Senior Data Operations Analyst

Role overview Lead data quality analysis for large machine learning annotation projects spanning visual, 3D point-cloud, and text data. The work combines statistical auditing, operational monitoring, and collaboration with research teams to improve annotation standards and explain quality issues.

Responsibilities - Develop sampling methods to assess annotation accuracy across complex datasets. - Build dashboards that monitor annotator agreement, quality indicators, and labeling speed. - Work with research partners to turn benchmark failures into clearer annotation guidelines. - Investigate disagreements and unusual cases to identify underlying causes. - Prepare evidence-based quality reports and certification findings.

Requirements - At least three years in data analytics, data operations, or machine-learning quality assurance. - Strong Python skills, including experience with Pandas and NumPy, plus SQL. - Experience with data visualization tools. - Understanding of annotation methods such as bounding boxes, polygon segmentation, named-entity recognition, and preference ranking. - Clear analytical writing and communication skills for distributed, asynchronous work.

Benefits and work setup - Full-time remote role based in India, with Bengaluru listed as a location option. - Annual compensation listed at ₹22,00,000–₹32,00,000, plus equity. - Learning and conference allowance, home-office stipend, and health benefits.